Combined Acoustic Imaging and Viscoelastic Parameters Estimation in Breast Cancer

The purpose of this research is to optimize and evaluate the efficacy of a hybrid imaging and quantitative viscoelasticity measurement tool for breast cancer detection and monitoring. The general goal of this project is to apply vibro-acoustography (VA) and the shear wave dispersion ultrasound vibrometry (SDUV) technique for characterizing breast lesions in specific applications where there is a need for improved imaging with higher specificity. The hypothesis is that by using combined VA-SDUV, researchers will be able to improve pre-biopsy breast lesion characterization.

The hybrid VA-SDUV prototype provides imaging as well as viscoelasticity properties of tissue using the same ultrasound probe. The proposed method is a low-cost, noninvasive tool anticipated to offer higher specificity than does conventional breast imaging methods; thus, it will reduce unnecessary breast biopsies and improve breast patient care.

Project aims include:

  • Optimize the VA-SDUV prototype for breast imaging and viscoelasticity measurement.
  • Determine diagnostic accuracy of combined use of VA and SDUV in breast lesion detection.
  • Assess the response to preoperative chemotherapy in breast cancer patients using the combined information from VA and SDUV.

For the first aim, the VA-SDUV prototype implemented on a programmable ultrasound system is optimized. For the second aim, the team performs VA and SDUV on patients with breast masses identified on magnetic resonance imaging (MRI). Since MRI has a high sensitivity in detecting breast lesions, estimation of VA sensitivity based on MRI is expected to be a good estimation of its true sensitivity. The common features associated with breast cancer lesions are identified, such as spiculation, architectural distortion, microlobulated lesion, or ill-defined lesion and presence of pleomorphic calcifications. SDUV provides a quantitative estimate of lesion elasticity and viscosity, which are important markers of malignancy. Combined information from VA and SDUV are used to differentiate breast lesions. Sensitivity and specificity of the proposed method will be calculated based on MRI and the result of pathology.

For the third aim, VA and SDUV imaging is performed on newly diagnosed breast cancer patients who are scheduled for preoperative chemotherapy. This process is repeated in the middle and after completion of the preoperative chemotherapy. The pre-, mid- and post-chemotherapy VA images are compared with the corresponding MRI scans to verify the capability of VA in estimating lesion downsizing. Changes in lesion appearance and viscoelastic parameters are then correlated to lesion size changes. The results are verified using the outcomes of MRI and biopsy.